Techniques for smoothing scripted stereo curves for stereoscopic computer animation

ABSTRACT

A computer-implemented method for smoothing a stereo parameter for a computer-animated film sequence. A timeline for the film sequence is obtained, the timeline comprising a plurality of time entries. A stereo parameter distribution is obtained, wherein the stereo parameter distribution comprises one stereo parameter value for at least two time entries of the plurality of time entries, and wherein the stereo parameter value corresponds a stereo setting associated with a pair of stereoscopic cameras configured to produce a stereoscopic image of the computer-animated film sequence. Depending on a statistical measurement of the stereo parameter distribution, either a static scene parameter is calculated, or a set of smoothed parameter values is calculated.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit under 35 U.S.C. 119(e) of priorcopending U.S. Provisional Patent Application No. 61/678,568, filed Aug.1, 2012, which is hereby incorporated by reference in the presentdisclosure in its entirety.

BACKGROUND

1. Field

The present disclosure relates generally to generating optimized stereosettings for computer animation, and more specifically to smoothingbounded-parallax constraints for a film sequence depicting acomputer-generated scene.

2. Related Art

Cinematographic-quality computer animation has evolved to produceincreasingly realistic and engaging visual effects. One way that this isaccomplished is through the use of stereoscopic filming techniques thatsimulate human binocular vision by presenting slightly differentviewpoints of a scene to a viewer's left and right eye. This technique,also known colloquially as “3D,” can be used to enhance the illusion ofdepth perception and make objects in a computer-generated scene appearto extend outward from a two-dimensional screen.

In normal human binocular vision, each eye views the world from aslightly different perspective. The difference in the view from eacheye, also called parallax, is caused, in part, by the spatial separationbetween the eyes. In general, the amount of parallax is increased forobjects that are closer to the viewer as compared to objects that arefurther from the viewer. The brain is able to combine the differentviews from each eye and use the parallax between views to perceive therelative depth of real-world objects.

Computer-animation stereoscopic filming techniques take advantage of thebrain's ability to judge depth through parallax by presenting separateimages to each eye. Each image depicts a computer-generated object froma slightly different viewpoint. The distance between the left and rightimages displayed on a screen (parallax) indicates the relative depth ofthe displayed computer-generated object. Parallax can be positive ornegative depending on whether the computer-generated object appears tobe behind the screen (positive parallax) or if it appears to be in frontof the screen (negative parallax).

In the real world, the amount of parallax between a viewer's left andright eyes is determined by two parameters, which are essentially fixed:the spacing between the eyes of the viewer and the distance from theviewer to the object. However, when composing stereo for acomputer-animated scene, a filmmaker (e.g., a director or stereographer)can adjust a broader range of stereoscopic parameters (scene parameters)to control the perception of depth in a computer-generated scene. Inparticular, a filmmaker may be able to adjust scene parameters thatdetermine the camera position, camera separation, camera convergence,and focal length of the lens to increase or decrease the stereo effect(perceived depth of a computer-generated object in a computer-generatedscene).

However, providing too much flexibility in the variability of too manyscene parameters may make it difficult for the filmmaker to control oroptimize the stereo effect for each shot in a computer-animatedsequence. In one traditional solution, many of the scene parameters arefixed or only allowed to vary within a range of hard limits. The fixedvalues or hard limits serve as a rule-of-thumb for filmmakers, but donot guarantee that stereo effect is satisfactory or comfortable to viewby an audience. Additionally, limiting the scene parameters to a fixedvalue or fixed range of values may under-utilize the design space whencomposing a computer-generated scene. In particular, fixed ranges limitthe filmmaker's ability to make trade-offs between the interrelatedscene parameters, which may limit the ability to produce dynamicthree-dimensional effects.

Another traditional solution is to provide the director or stereographerwith direct control over the scene parameters for each scene in a film.This approach also has drawbacks in that it may be difficult to finetune all of the scene parameters to achieve the desired amount of stereoeffect. Too little stereo effect and the objects in the scene willappear flat. Too much stereo effect and the objects may appear distortedor the scene may become uncomfortable to view. Additionally, becausethis approach relies on manual input, the stereo effect may beinconsistent throughout the film sequence, especially when stereoadjustments are applied to a particular scene but not to others.

What is needed is a technique for consistently achieving an optimalstereo effect without the drawbacks of the traditional approachesdiscussed above.

SUMMARY

One exemplary embodiment includes a computer-implemented method forsmoothing a stereo parameter for a computer-animated film sequence. Atimeline for the film sequence is obtained, the timeline comprising aplurality of time entries. A stereo parameter distribution is obtained,wherein the stereo parameter distribution comprises one stereo parametervalue for at least two time entries of the plurality of time entries,and wherein the stereo parameter value corresponds a stereo settingassociated with a pair of stereoscopic cameras configured to produce astereoscopic image of the computer-animated film sequence. A statisticalmeasurement of the stereo parameter distribution is calculated. If thestatistical measurement is less than a threshold value: a static sceneparameter is calculated based on the stereo parameter values of theparameter distribution. The static scene parameter is stored in acomputer memory as the stereo parameter value for each of the at leasttwo time entries. If the statistical measurement is greater than orequal to a threshold value, a set of smoothed parameter values iscalculated based on the parameter distribution and a smoothing function.The set of smoothed parameter values are stored in computer memory asthe stereo parameter value for each of the at least two time entries.

In some exemplary embodiments, each camera of the pair of stereoscopiccameras is positioned relative to each other based on the smoothedparameter values. A stereoscopic film sequence of the computer-generatedscene is created with the pair of stereoscopic cameras. The stereoscopicfilm sequence is stored in the computer memory.

In some exemplary embodiments, a camera separation value and aconvergence value for the pair of stereoscopic cameras are calculatedbased on script-adjusted near-parallax value and script-adjustedfar-parallax value. The camera separation value and the convergencevalue are stored in the computer memory. In some cases, each camera ofthe pair of stereoscopic cameras is positioned relative to each otherwithin the computer-generated scene based on the camera separation valueand the convergence value. In some cases, a camera sensor of the pair ofstereoscopic cameras is positioned within the computer-generated scenebased on the camera separation value and the convergence value.

In some embodiments, if the statistical measurement is less than athreshold value, the static scene parameter is calculated by taking anaverage of the stereo parameter values of the parameter distribution. Insome cases, if the statistical measurement is less than a thresholdvalue, the static scene parameter is calculated by taking a statisticalmean of the stereo parameter values of the parameter distribution. Insome cases, if the statistical measurement is greater than a thresholdvalue, the set of smoothed parameter values is calculated based on theparameter distribution and a low-pass filter function.

DESCRIPTION OF THE FIGURES

FIG. 1 depicts a stereoscopically filmed, computer-generated scene.

FIGS. 2A and 2B depict exemplary configurations for stereoscopicallyfilming a computer-generated scene.

FIG. 2C depicts an exemplary configuration for displaying astereoscopically filmed scene.

FIG. 3 depicts an exemplary process for determining a set of sceneparameters using baseline stereo settings.

FIG. 4 depicts an exemplary computer-animated scene filmed by a pair ofstereoscopic cameras.

FIG. 5 depicts an exemplary process for adjusting a set of sceneparameters based on a user's selection of stereo volume and stereoshift.

FIG. 6 depicts an exemplary process for adjusting a set of sceneparameters based on a stereo depth script.

FIG. 7 depicts a graphical representation of an exemplary stereo depthscript.

FIG. 8 depicts an exemplary process for filtering a set of sceneparameters for a sequence of images in a film sequence.

FIG. 9 depicts exemplary stereo curves for a film sequence.

FIG. 10 depicts an exemplary computer system.

DETAILED DESCRIPTION

The following description is presented to enable a person of ordinaryskill in the art to make and use the various embodiments. Descriptionsof specific devices, techniques, and applications are provided only asexamples. Various modifications to the examples described herein will bereadily apparent to those of ordinary skill in the art, and the generalprinciples defined herein may be applied to other examples andapplications without departing from the spirit and scope of the variousembodiments. Thus, the various embodiments are not intended to belimited to the examples described herein and shown, but are to beaccorded the scope consistent with the claims.

FIG. 1 depicts a stereoscopically filmed, computer-generated scene. Thescene depicts two animated characters viewed in profile. For purposes ofthis discussion, each animated character is treated as a singlecomputer-generated object. The image depicted in FIG. 1 is a compositeof two views of the computer-generated scene: one view from a leftcamera and one view from a right camera. The left and right camera viewscan be used to produce a stereoscopic image of the computer-generatedscene. In a typical case, the cameras used to produce the left and rightviews are offset a distance that corresponds to an estimated distancebetween the viewer's eyes (approximately 65 mm).

The image in FIG. 1 appears slightly blurred because the animatedcharacters (exemplary computer-generated objects) are viewed from theslightly different positions of the left and right camera. However, whenthe image is viewed with appropriate stereoscopic equipment, theleft-camera view is presented to the viewer's left eye in isolation andthe right-camera view is presented to the viewer's right eye inisolation. This can be achieved using a number of techniques that areknown in the art, including, for example, use of stereoscopic glasses.Using these known techniques, the left-camera view is separatelypresented to the left eye using polarized or color-coded light thatcorresponds to a polarized or color-coded left lens of the stereoscopicglasses. Similarly, the right-camera view is separately presented to theright eye using polarized or color-coded light that is distinguishablefrom the left-camera view.

The viewer is able to mentally and visually combine the left-camera andright-camera view into a composite image that includes a certain degreeof parallax for one or more computer-generated objects. The greater theparallax, the closer/farther the computer-generated object appears tothe viewer (with respect to the display screen). As discussed above, afilmmaker can use this stereo effect to make computer-generated objectsappear to have depth even though they are displayed on what isessentially a two-dimensional display screen.

To create a stereoscopic film sequence, the computer-generated scene canbe animated using traditional computer-animation techniques and thescene can be stereoscopically filmed. The resulting stereoscopic filmsequence comprises a series of image frames, each image framerepresenting the computer-generated scene at a point in time. When theseries of image frames are presented to a viewer, the computer-generatedscene can be made to depict a live action scene appearing to have depthdue to the stereoscopic effect of the filming technique.

1. Filming and Viewing a Stereoscopic Computer-Generated Scene

FIGS. 2A and 2B depict exemplary optical configurations of astereoscopically filmed computer-generated scene in camera space. Theconfigurations include a left camera (202, 212) and a right camera (204,214) that are capable of viewing a point (210, 220) on an object in acomputer-generated scene. FIGS. 2A and 2B depict alternativeconfigurations for positioning the cameras when filming thecomputer-generated scene. FIG. 2A depicts a converged cameraconfiguration with the cameras 202 and 204 pointed inward at an angle βand converging along a curved convergence surface. FIG. 2B depicts analternative configuration with cameras 212 and 214 pointed in a paralleldirection and having sensors (216, 218) offset from the center of theirrespective lens at a distance h. In FIG. 2B, the parallel cameras 212and 214 converge along a convergence plane. Either of the cameraconfigurations shown in FIGS. 2A or 2B can be used to stereoscopicallyfilm a computer-generated scene.

With reference to FIG. 2A, the left and right cameras (202, 204) eachrecord a different image of the computer generated scene, which includespoint 210. The left camera 202 records an image of the point 210 atleft-image location (S_(lx), S_(ly)) using the left camera sensor 206.Similarly, the right camera 202 records an image of the point 210 atright-image location (S_(rx), S_(ry)) using the right camera sensor 208.The difference between the left-image location (S_(lx), S_(ly)) and theright-image location (S_(rx), S_(ry)) indicates the amount of parallaxfor point 210. Similarly, with reference to FIG. 2B, the left and rightcameras (212, 214) each record a different image of the point 220 atleft-image location (S_(lx), S_(ly)) for left sensor 216 and theright-image location (S_(rx), S_(ry)) for right sensor 218.

FIGS. 2A and 2B also depict several scene parameters that have an impacton how computer-generated objects or points in the computer-generatedscene will be perceived by the viewer. The three-dimensional scenecoordinate (C_(x), C_(y), C_(z)) describes the location of the point 210within the computer-generated scene. Convergence distance c is thedistance from the lenses and the convergence surface or convergenceplane. The convergence surface/plane corresponds to the location ofpoints that will have zero parallax between the left and right images.Also, points located further away from the convergence surface/planewill have greater parallax than those points that are closer to theconvergence surface/plane. The camera separation t represents thedistance between optical nodes of the left and right cameras, and mayalso have an impact on the amount of parallax. The left and rightcameras also have sensor width W_(c) and a focal length f from thesensor to the lens.

FIG. 2C depicts an exemplary configuration of a stereoscopically filmedcomputer-generated scene in viewer space. In general, viewer spacerepresents how a stereoscopically filmed, computer-generated scene maybe perceived by a modeled viewer located a specified distance from amodeled screen. As shown in FIG. 2C, the modeled viewer has aninter-ocular distance e and is positioned a distance V_(z) from themodeled screen having a screen width W_(s). FIG. 2C depicts how left andright views, each presented to the modeled viewer's left and right eyerespectively, result in eye convergence that simulates the points asbeing out of plane from the screen. Specifically, FIG. 2C depictsperceived point 310 that appears to be behind the screen plane, andperceived point 320 that appears to be in front of the screen plane.

Perceived point 310 is represented by left-camera image 312 andright-camera image 314. Because the left-camera image 312 is to the leftof right-camera image 314, the perceived point 310 is said to havepositive parallax and will appear to the viewer to have a depth that isgreater than the distance from the viewer to the screen V_(z). In otherwords, to the viewer, the perceived point 310 will appear to existbehind the screen plane.

Similarly, perceived point 320 is represented by left-camera image 322and right-camera image 324. Because the left-camera image 322 is to theright of right-camera image 324, the perceived point 320 is said to havenegative parallax and will appear to the viewer to have a depth that isless than the distance from the viewer to the screen V_(z). In otherwords, to the viewer, the perceived point 320 will appear to exist infront of the screen plane.

One technique for simplifying the stereo configuration is to describe aset of bounded-parallax constraints. A set of bounded-parallaxconstraints typically includes a far-parallax value, a near-parallaxvalue, a near distance, a far distance, and a focal length. Thefar-parallax value is the maximum positive parallax for thecomputer-generated scene and is typically expressed in terms of pixelsor a percentage of screen width. Similarly, the near-parallax value isthe minimum negative parallax for the computer-generated scene and isalso typically expressed in terms of pixels or a percentage of screenwidth. The near distance and far distance are the near and far limits ofwhere computer-generated objects may be placed within thecomputer-generated scene. Focal length is the focal length of the pairof stereoscopic cameras and is depicted as f in FIGS. 2A and 2B, above.

The amount of stereo effect perceived by the viewer can be controlled bymanipulating the bounded-parallax constraints or the other sceneparameters discussed above with respect to FIGS. 2A and 2B. Ideally, thescene parameters (e.g., the bounded-parallax constraints) are set toproduce an optimum stereo effect for at least one of thecomputer-generated objects in the scene. However, because thecomposition of a computer-generated scene can vary and the desiredamount of stereo effect may vary, the scene parameters and the optimalparameter settings may also vary over the course of computer-animatedfilm sequence. As previously mentioned, one solution is to manuallyadjust the scene parameters to suit the requirements for each scene.However, this approach typically requires the direct involvement of askilled director or stereographer to ensure that the settings areappropriate. Even then, it may be difficult to maintain consistencyacross scenes in a film or across films produced from the same studio.

Therefore, it is generally desirable to automate at least a portion ofthe scene parameter setting process while still providing the filmmakerwith creative control, when necessary. The system and techniquesdiscussed below can be used to determine optimal scene parametersettings and position the stereoscopic cameras within the scene toobtain an optimized and consistent stereo effect.

2. Setting Baseline Scene Parameters

FIG. 3 depicts a flow chart of an exemplary process 1100 for determiningthe bounded-parallax constraints for the placement for a pair ofstereoscopic cameras in a computer-generated scene using baseline stereosettings. In general, process 1100 can be used to determine acceptablestereo settings for a particular computer-generated scene based on oneor more tables of baseline stereo settings. The one or more tables ofbaseline stereo settings are typically formulated in advance and includegroupings of stereo parameters (stereo setting entries) that are knownto produce an acceptable stereo effect for a particular scene layout. Insome cases, the one or more tables of baseline stereo settings aremanually created by a stereographer or director having skill inconfiguring stereo settings for a scene.

For purposes of the following discussion, it is assumed that acomputer-generated scene includes at least one computer-generatedobject, which is in view of at least one camera of a pair ofstereoscopic cameras. For process 1100, reference is made to FIG. 4,which depicts an exemplary computer-generated scene 400 with twoanimated characters (450, 452) (exemplary computer-generated objects) inview of a pair of stereoscopic cameras (402, 404). Each camera has acamera sensor (406, 408) positioned (centered or offset) with respect toa lens having a focal length f. The field of view of the stereoscopiccameras is determined, in part, by the focal length f of the cameralenses and defines the visual boundaries of the computer-generatedscene.

With reference to FIG. 3, in operation 1102, the minimum scene depth iscalculated. In the following example, the minimum scene depth is basedon the distance from the cameras to the nearest point of interest in acomputer-generated scene. For a computer-generated scene having a singlecomputer-generated object, the nearest point of interest may be thepoint on the computer-generated object that is closest to the camera.

FIG. 4 depicts an exemplary configuration for a computer-generated scene400 having two computer-animated characters (450, 452) positioned withrespect to cameras (402, 404). Distance 420 represents the distance fromthe pair of cameras (402, 404) to the nearest point 455 on the nearestanimated character in the scene 400. In this example, distance 420 ismeasured from the midpoint between the pair of cameras (402, 404) to apoint 455 on the nearest animated character 450. Other points related tothe location of the pair of cameras (402, 404), including, for example,the location of the camera sensors (406, 408) or the location of thelenses, could also be used as reference points for the distance to thenearest point 455.

In general, to produce a satisfactory stereo effect over a series ofimages in a film sequence using process 1100, it is advantageous toselect a point of interest that is both associated with a subject of aviewer's attention and will remain relatively consistent across theseries of images. If a consistent point of interest is not selected overa series of images, the camera placement may appear erratic or jumpy.

A number of techniques can be used to determine the nearest point ofinterest that satisfied these criteria. In one example, the nearestpoint of interest in a computer-generated scene can be determined byscanning or sampling the computer-generated scene over a projected areaassociated with a middle portion of the camera sensor.

With reference to FIG. 4, the projected area associated with a middleportion of the sensor can be determined based on the field of view ofthe pair of stereoscopic cameras. As depicted in FIG. 4, the pair ofcamera sensors (406, 408) is associated with a primary projected area410 defined, in part, by the field of view of the pair of cameras (402,404). The primary projected area 410 roughly corresponds to the completeimage that will be captured by the cameras and presented to the viewer.The primary projected area 410 typically includes transient objects likebrush, leaves, and the ground effects that may change over the filmsequence. Thus, in some cases, selecting a nearest point of interestbased on the location of these transient objects may produce a minimumscene depth that changes rapidly and results in a jumpy stereo effect.These transient objects are also typically located near the periphery ofthe primary projected area 410 and are also not likely to be subject ofthe viewer's attention. For example, the transient objects may includeobjects on the ground or foliage that surrounds the primary subjects onthe scene.

To address this problem, a second projected area associated with themiddle portion of the camera sensor can be used to determine the minimumscene depth. As shown in FIG. 4, a secondary projected area 411associated with a middle portion of the pair of camera sensors isdefined. The secondary projected area 411 typically includes the subjectof the viewer's attention and excludes many of the transient objectsincluded in the periphery of the primary projected area 410. The size ofthe secondary projected area 411 can be determined in order to produceminimum scene depth that will be consistent across the film sequence andwill also correspond to the subject of the viewer's attention. In theexample depicted in FIG. 4, the size of the secondary projected area 411is approximately ⅔ of the field of view of the pair of cameras (orapproximately ⅔ of the size of the primary projected area 410). In othercases, the secondary projected area 411 may be, for example,approximately ¾, ½, ¼, or any other fractional size of the field of viewof the pair of cameras.

The secondary projected area 411 may be scanned or sampled for thenearest point of interest. In one example, a depth array of depth pixelsis defined over the secondary projected area 411. Each depth pixel isassociated with a depth value representing, for example, a distance fromthe pair of cameras to the nearest intersecting object in the scene asmeasured along an imaginary line that originates at one or more camerasensor pixels and passes through the corresponding depth pixel in thedepth array. If an intersecting object is not present for the depthpixel, the depth value may be empty or zero. Using a depth array, ascanning algorithm may be implemented that finds the lowest non-zero ornon-empty depth value in the depth array and stores that value as thenearest point of interest. Alternatively, a sampling algorithm may beimplemented that selects a subset of the depth pixels in the deptharray, finds the lowest non-zero or non-empty depth value, and storesthat value as the nearest point of interest.

In another example, one or more computer-generated objects may be taggedas important for the scene. For example, an animated character may bemanually tagged by the filmmaker as important because the animatedcharacter is the subject of the scene or film sequence. In thisembodiment, the nearest point on the nearest tagged computer-generatedobject with respect to the pair of cameras is used as the nearest pointof interest.

With reference again to FIG. 3, in operation 1104, a near-parallax value(or near shift ns) is calculated based on a set of baseline stereosettings. As previously mentioned, the near-parallax value typicallyrepresents the maximum negative parallax between left and right views ofa computer-generated object in the scene. The set of baseline stereosettings includes multiple stereo-setting entries of setting parametervalues that are known to produce a satisfactory stereo effect.Specifically, each stereo-setting entry specifies a recommended scenedepth, a recommended focal length, and a recommended near-parallaxvalue. The multiple stereo-setting entries may be determined in advanceand stored in a database or series of tables. As previously mentioned,the stereo-setting entries may be manually created in advance by astereographer or director having skill in configuring stereo settingsfor a scene.

In the present embodiment, the near-parallax value is calculated byselecting a stereo-setting entry having a recommended scene depth thatcorresponds to the minimum scene depth (determined in operation 1102)and having a recommended focal length that corresponds to the focallength of the pair of cameras. The near-parallax value is calculatedbased on the recommended near-parallax value of the selectedstereo-setting entry.

In general, the set of baseline stereo settings is stored to facilitatethe selection of a stereo-setting entry given two of the threerecommended values. In an exemplary storage configuration, pairs ofrecommended near-parallax values and associated recommended scene depthsare stored in a table of stereo-setting entries. Multiple tables ofstereo-setting entries are created, each table associated with arecommended focal length. Using this storage configuration, a tableassociated with a recommended focal length can be selected based on thefocal length of the pair of cameras. Within the selected table, astereo-setting entry having a recommended scene depth that correspondsto the minimum scene depth (determined in operation 1102) can beselected. The near-parallax value can then be determined based on therecommended near-parallax value of the selected stereo-setting entry.

In many cases, the selected table will not have a recommended scenedepth that exactly matches the minimum scene depth. In this case, two ormore stereo-setting entries may be selected and the near-parallax valuecan be determined by interpolating between two or more parameter valuesassociated with the selected stereo-setting entries. Similarly, when thefocal length of the cameras falls between recommended focal lengthsassociated with the tables of entries, recommended parameter values frommultiple focal length tables can be used to interpolate thenear-parallax value.

In this way, if the minimum scene depth and focal length of the camerasare known, a precise value for the near-parallax value can becalculated. In the present embodiment, the set of baseline stereosettings includes recommended focal lengths ranging from 14 mm to 200 mmand recommended scene depths ranging from 0.4 to 100,000 length units.

Typically, the selection and interpolation of stereo-setting entries areperformed by a single function call that takes the focal length andminimum scene depth as inputs and returns a near-parallax value.Equation 1, below, depicts an exemplary function “StereoLUT” thatperforms these functions.

ns=stereoLUT(nd, f),   (1)

where nd is the minimum scene depth (determined in operation 1102), f isthe focal length of the pair of cameras, and ns is the near-parallaxvalue (or near shift).

In operation 1106, a far-parallax value is calculated based on the focallength of the lenses of the pair of cameras. The far-parallax valuetypically represents the maximum positive parallax between left andright views of a computer-generated object in the scene. In the presentembodiment, the far-parallax value is based on the focal length of thepair of cameras. Equation 2 below depicts an exemplary relationshipbetween the far-parallax value and focal length.

fs=K*f,   (2)

where fs is the far-parallax value (or far shift), f is the focal lengthof the pair of cameras, and K is a scalar value. In the presentembodiment, K is 1.0, resulting in a far-parallax value that equals thefocal length of the pair of cameras.

In operation 1108, the near-parallax value and far-parallax value arestored. The values are typically stored and associated with the otherbounded-parallax constraints (e.g., near distance, far distance, andfocal length) that specify the stereo settings for an image or frame ina film sequence. The values may be stored, for example, on anon-transitory computer-readable storage medium, such as a computerstorage disk. Other computer storage examples are provided below anddiscussed with respect to FIG. 10.

The near-parallax and far-parallax values can be used to calculate otherstereoscopic parameters for the computer-generated scene. For example, acamera separation value and a convergence value can be calculated forthe pair of cameras based on the far-parallax value and thenear-parallax value. Equation 3, below, depicts an exemplary techniquefor calculating a camera separation value t using far-parallax andnear-parallax values.

$\begin{matrix}{{t = {\frac{{{nd}*{fs}*{fd}} - {{fd}*n\; s*{nd}}}{{fd} - {nd}}*\frac{W_{c}}{f*R_{c}}}},} & (3)\end{matrix}$

where W_(c) is the camera sensor width, R_(c) is the resolution of thecamera sensor, nd is the minimum scene depth (near distance), fs is thefar-parallax (far shift), fd is the maximum scene depth (far distance),and ns is the near-parallax (near shift).

Equation 4, below, depicts an exemplary technique for calculating aconvergence distance value c using far-parallax and near-parallaxvalues.

$\begin{matrix}{c = {\frac{{{nd}*{fs}*{fd}} - {{fd}*n\; s*{nd}}}{{{fd}*{fs}} - {{nd}*n\; s}}.}} & (4)\end{matrix}$

The camera separation value and a convergence distance value may also bestored, for example, on a non-transitory computer-readable storagemedium, such as a computer storage disk. Other computer storage examplesare provided below and discussed with respect to FIG. 10.

The camera separation value t and the convergence distance value c maybe used to position the pair of stereoscopic cameras in thecomputer-generated scene. For example, as discussed above, FIG. 2Adepicts a converged camera configuration with the cameras 202 and 204separated by a distance t and pointed inward at an angle β andconverging along a curved convergence surface that is a convergencedistance c from the cameras. FIG. 2B depicts an alternativeconfiguration with cameras 212 and 214 also separated a distance t andpointed in a parallel direction. In FIG. 2B, the camera sensors (216,218) are offset from the center of their respective lens at a distance hand the parallel cameras 212 and 214 converge along a convergence planethat is a convergence distance c from the cameras. The convergenceprinciples shown in FIGS. 2A and 2B can also be combined to produce aconvergence configuration with the cameras both pointed inward at anangle β and having sensors offset a distance h. Equations 5 and 6,below, demonstrate the relationship between the convergence value c andparameters that directly specify the position of the pair ofstereoscopic cameras.

$\begin{matrix}{{h = {2f\; {\tan \left( {{\arctan \left( \frac{t}{2c} \right)} - \beta} \right)}}},{and}} & (5) \\{{\beta = {{\arctan \left( \frac{t}{2c} \right)} - {\arctan \left( \frac{h}{2f} \right)}}},} & (6)\end{matrix}$

where f is the focal length of the pair of cameras, t is the cameraseparation value, and c is the convergence distance value. Thus, usingthe camera separation value t and the convergence distance value c, thepair of stereoscopic cameras can be positioned within acomputer-generated scene.

Using the new placement of the pair of stereoscopic cameras, astereoscopic image of the computer-generated scene can be captured bythe camera sensors. The image may be saved as a single image, orassociated with a frame or time entry in an animated film sequence.Typically, a series of stereoscopic images are captured as thecomputer-generated objects in the computer-generated scene aremanipulated to produce a computer animation sequence.

The bounded-parallax constraints calculated using process 1100,discussed above, may remain the same throughout a given computeranimation sequence. However, in some cases, the bounded-parallaxconstraints or the placement for a pair of stereoscopic cameras maychange one or more times during the computer animation sequence. Forexample, if the objects in the computer generated scene move toward oraway from the pair of stereoscopic cameras, the distance to the nearestpoint in the scene may change (e.g. point 455 in FIG. 4). In some cases,it may be beneficial to recalculate the bounded-parallax constraintsbased on an updated distance to the nearest point by repeating process1100. Similarly, bounded-parallax constraints may be re-calculated for achanging focal length. For example, the focal length may change due tochanges in the settings of a zoom lens.

As discussed above, the stereoscopic image or images (produced usingbounded-parallax constraints calculated with process 1100) can bedisplayed to a viewer using known stereoscopic techniques to produce ascene appearing to have depth in and out of the screen. For example, thestereoscopic image may be displayed to a viewer who is viewing the imagethrough stereo glasses.

Process 1100 can be combined with other automated processes forproducing or refining scene parameters for a stereoscopically filmedscene. For example, U.S. Provisional Application No. 61/678,568describes exemplary processes for calculating scaled parallaxconstraints, creative control of parallax constraints, scripted parallaxconstraints, and other parameters that can be combined with process1100, described above. Combining multiple processes may produce stereosettings that result in an optimal stereo effect and are more consistentacross a film sequence, as compared to traditional manual stereo-settingtechniques.

3. Adjusting Scene Parameters Based on Stereo Volume and Stereo Shift

Process 1100, described above, provides an automated technique forsetting the amount of stereo for a particular shot. In some cases, it isalso desirable to provide the filmmaker with creative control over theamount of stereo for a particular shot. That is, for one or more imagesof a computer-generated scene, the amount of stereo may need to beboosted (amplified) or crushed (attenuated) to achieve the desiredstereo effect. Additionally, the filmmaker may want to shift theconvergence distance (point of zero parallax) forward or backward toemphasize or deemphasize certain aspects of the scene.

One solution is for the filmmaker to directly manipulate the sceneparameters used to specify the location of the pair of stereoscopiccameras within the scene. For example, by adjusting the cameraseparation, camera sensor offset, distance to the objects, andconvergence angle, the filmmaker can effect changes in the amount ofstereo. However, the relationship between various scene parameters maybe complex and, therefore, it may be difficult for the filmmaker todirectly manipulate the parameter values to achieve a particular stereoeffect.

Another solution is to specify changes to an existing stereoconfiguration in terms of a stereo volume and stereo shift, as describedbelow with respect to FIG. 5. In particular, FIG. 5 depicts an exemplaryprocess 1300, for determining creative parallax constraints for acomputer-generated scene based on user-specified stereo-volume andstereo-shift values. Process 1300 can be used to creatively control theamount of stereo for a given shot without requiring that the filmmakermanually manipulate the position of the cameras.

With respect to FIG. 5, in operation 1302, scene parameters for acomputer-generated scene are obtained. The scene parameters may include,for example, two bounded-parallax constraints: a near-parallax value anda far-parallax value. These values may be obtained from computer memoryor they may be obtained as an output of another process. As discussedabove, process 1100 can be used to obtain near-parallax and far-parallaxvalues.

Alternatively, the near-parallax and far-parallax values may be obtainedbased on an existing computer-generated scene configuration having apair of stereoscopic cameras placed with respect to one or morecomputer-generated objects. As discussed above with respect to FIGS. 2Aand 2B, scene parameters, namely, camera separation t, convergencedistance c, focal length f, and sensor width W_(c), can be used todescribe the stereoscopic configuration of a computer-generated scene.Equations 7 and 8, below, can be used to calculate the near-parallaxvalue ns and far-parallax value fs given a set of other sceneparameters.

$\begin{matrix}{{{n\; s} = {\left( \frac{{fR}_{c}}{W_{c}} \right)\left( {\frac{t}{c} - \frac{t}{nd}} \right)}},{and}} & (7) \\{{{fs} = {\left( \frac{{fR}_{c}}{W_{c}} \right)\left( {\frac{t}{c} - \frac{t}{fd}} \right)}},} & (8)\end{matrix}$

where f is the focal length of the pair of cameras, R_(c) is theresolution of the camera sensors, W_(c) is the width of the camerasensors, t is the camera separation, c is the convergence distance, ndis the minimum scene depth, and fd is the maximum scene depth.

With reference again to FIG. 5, in operation 1304, a stereo-volume valueV and a stereo-shift value S are obtained from the user. These valuesmay be obtained from a user using an input device, such as a computerkeyboard or other computer input hardware device. Exemplary computerinput devices are described below with respect to computer system 2000in FIG. 10. Typically, the stereo-volume value V is expressed as apercentage of parallax. A stereo-volume value less than 100 percent istypically associated with an attenuation of the stereo effect.Similarly, a stereo-volume value greater than 100 percent is typicallyassociated with an amplification of the stereo effect. The stereo-shiftvalue S is expressed in terms of a distance normalized by the width orresolution of the screen. For example, the stereo-shift S may beexpressed in terms of a number of pixels, where the number of pixelsrepresents the distance across the screen or camera sensor. A positivestereo-shift value is typically associated with movement of theconvergence plane toward from the pair of stereoscopic cameras and anegative value is typically associated with a movement of theconvergence plane away from the pair of stereoscopic cameras.

In operations 1306 and 1308, creative scene parameters are calculatedusing the stereo-volume value V and the stereo-shift value S obtained asuser input. Equations 9 and 10, below, depict an exemplary approach forcalculating a creative near-parallax value ns_creative and creativefar-parallax value fs_creative based on the stereo-volume value V andthe stereo-shift value S.

ns_creative=(ns*V)+S, and   (9)

fs_creative=(fs*V)+S,   (10)

where ns is the near-parallax value obtained in operation 1302, fs isthe far-parallax value obtained in operation 1302, Vis the stereo-volumevalue obtained in operation 1304, and S is the stereo-shift valueobtained in operation 1304.

As previously discussed, a stereo-volume value greater than 100 percentwill increase both the near-parallax and far-parallax values, resultingin an amplified or boosted stereo effect. A stereo-volume value lessthan 100 percent will decrease both the near-parallax and far-parallaxvalues, resulting in an attenuated or crushed stereo effect. Thestereo-shift value will move the stereo effect toward or away from thepair of stereoscopic cameras. A positive stereo-shift value isassociated with a movement of the convergence plane toward the camerasand will tend to make stereoscopically displayed computer-generatedobjects appear to have greater stereo effect into the display screen.Similarly, a negative stereo-shift value is associated with a movementof the convergence plane away from the cameras and typically results ina greater stereo effect out of the display screen.

In operation 1310, the creative near-parallax and far-parallax valuesare stored in computer memory. The creative near-parallax and creativefar-parallax values may be stored, for example, on a non-transitorycomputer-readable storage medium, such as a computer storage disk. Othercomputer storage examples are provided below and discussed with respectto FIG. 10.

In addition, the creative near-parallax and far-parallax values can alsobe used to calculate other stereoscopic parameters for thecomputer-generated scene. For example, equations 3 and 4, discussedabove, can be used to calculate a camera separation value and aconvergence value for the pair of cameras based on the creativenear-parallax and far-parallax values.

As previously discussed, the camera separation value t and theconvergence distance value c may be used to position the pair ofstereoscopic cameras in the computer-generated scene. Specifically,equations 5 and 6, discussed above, demonstrate the relationship betweenthe convergence value c and parameters that directly specify theposition of the pair of stereoscopic cameras. Thus, stereo volume andstereo shift can be used to determine a camera separation value t andthe convergence distance value c, which can be used to position the pairof stereoscopic cameras within a computer-generated scene.

Using the new placement of the pair of stereoscopic cameras, astereoscopic image of the computer-generated scene can be captured bythe camera sensors. The image may be saved as a single image orassociated with a frame in an animated film sequence. As discussedabove, the stereoscopic image can be displayed to a viewer using knownstereoscopic techniques (e.g., stereo glasses) to produce a sceneappearing to have depth in and out of the screen.

4. Adjusting Scene Parameters Based on a Stereo Depth Script

As previously discussed, a computer-animated film sequence can becreated by animating a computer-generated scene and stereoscopicallyfilming the animated scene using a pair of stereoscopic cameras. Theresulting stereoscopic film sequence comprises a series of image frames,each image frame representing the computer-generated scene along afilm-sequence timeline.

FIG. 7 depicts a composite image 802 that represents a film sequence asa computer-animated scene changes over time. Below the composite image802, FIG. 7 depicts a graphical representation of a film-sequencetimeline 810 having a plurality of time entries 812. Each time entryrepresents a moment in time and is associated with corresponding imageframe in the film sequence. Each time entry is also associated with aset of scene parameters that specify, inter alia, the placement of thestereoscopic cameras within the scene, and thus determines the stereoeffect for the film sequence.

The stereo effect can be modified over time based on a stereo script 820that specifies a stereo-volume curve 822 and a stereo-shift curve 824that corresponds to the film-sequence timeline 810. As discussed above,stereo volume and stereo shift can be used to amplify or attenuate theamount of stereo in a particular shot.

FIG. 6 depicts an exemplary process 1400 for calculating script-adjustedstereo parameters for a computer-animated film sequence. Using process1400 a filmmaker can specify how the stereo effect changes over time andproduce a complete stereo experience that is adapted for the storylineof the film sequence. Specifically, using a stereo-volume curve 822 andstereo-shift curve 824 (depicted in FIG. 7), process 1400 can be used toproduce a scripted stereo curve 830 for the film sequence.

In operation 1402, a film-sequence timeline is obtained for the filmsequence. The film-sequence timeline includes a plurality of timeentries that are associated with a plurality of image frames in the filmsequence. Typically, the time entries represent 1/24 second timingintervals along the film-sequence timeline. This time intervalcorresponds to the frame rate of a traditional film camera and can beused to produce cinematographic-quality film motion. Other timeintervals may be used and it is not necessary that the time intervals beregularly spaced along the film-sequence timeline.

In operation 1404, a stereo-volume value and a stereo-shift value areobtained for at least two time entries of the plurality of time entries.The stereo-volume and stereo-shift values may be obtained based on astereo-volume curve 822 and stereo-shift curve 824 (depicted in FIG. 7)that define the stereo-volume and stereo-shift over the film-sequencetimeline 810. The stereo-volume curve 822 and stereo-shift curve 824 maybe predefined by a filmmaker or director as a stereo script for the filmsequence.

Similar to process 1300 discussed above, the stereo-volume value istypically expressed as a percentage. A stereo-volume value less than 100percent is typically associated with an attenuation of the stereo effectand a stereo-volume value greater than 100 percent is typicallyassociated with an amplification of the stereo effect. Also similar toprocess 1300, the stereo-shift value S is typically expressed in termsof a distance normalized by the width or resolution of the screen andmay be expressed in terms of a number of pixels, where the number ofpixels represents the distance across the screen or camera sensor. Apositive stereo-shift value is typically associated with movement of theconvergence plane towards the pair of stereoscopic cameras and anegative value is typically associated a movement of the convergenceplane away from the pair of stereoscopic cameras.

In operation 1406, a set of scene parameters are obtained for the atleast two time entries. In this example, a near-parallax value and afar-parallax value are obtained for each of the at least two timeentries. These values may be obtained from computer memory or they maybe obtained as an output of another process. As discussed above,processes 1100, 1200, and 1300 can all be used to obtain near-parallaxand far-parallax values.

Alternatively, the near-parallax and far-parallax values may be obtainedbased on the existing computer-generated scene configuration associatedwith each of the at least two time entries. In particular, equations 7and 8 discussed above, can be used to calculate the near-parallax valuens and far-parallax value fs given a set of other scene parameters,including the focal length of the pair of cameras f, the resolution ofthe camera sensors R_(c), the width of the camera sensors W_(c), thecamera separation t, the convergence distance c, the minimum scene depthnd, and the maximum scene depth fd.

In operation 1408, script-adjusted scene parameters are calculated basedon the stereo-volume value and stereo-shift value for each of the atleast two time entries. Equations 11 and 12, below, depict an exemplaryapproach for calculating a script-adjusted near-parallax value ns_scriptand script-adjusted far-parallax value fs_script based on thestereo-volume value V and the stereo-shift value S.

ns_script=(ns*V)+S, and   (11)

fs_script=(fs*V)+S,   (12)

where ns is the near-parallax value obtained in operation 1406, fs isthe far-parallax value obtained in operation 1406, V is thestereo-volume value obtained in operation 1404, and S is thestereo-shift value obtained in operation 1404.

In operation 1410, the script adjusted scene parameters are stored incomputer memory. The script-adjusted near-parallax and far-parallaxvalues may be stored, for example, on a non-transitory computer-readablestorage medium, such as a computer storage disk. Other computer storageexamples are provided below and discussed with respect to FIG. 10.

Typically, the script-adjusted near-parallax and far-parallax values canalso be used to calculate other stereoscopic parameters for multipletime entries in the film-sequence timeline. An exemplary stereo curve830, depicted in FIG. 7 represents one of the stereoscopic parameters(near-parallax or far-parallax) as a function of time. As discussedabove, equations 3 and 4 can be used to calculate a camera separationvalue and a convergence value for the pair of cameras based on thenear-parallax and far-parallax values.

As previously discussed, the camera separation value t and theconvergence distance value c may be used to position the pair ofstereoscopic cameras in the computer-generated scene. Specifically,equations 5 and 6, discussed above, demonstrate the relationship betweenthe convergence value c and parameters that directly specify theposition of the pair of stereoscopic cameras. By calculating a positionfor the pair of cameras for multiple time entries in the film-sequencetimeline, the camera position can be animated to produce the desiredstereo effect that corresponds to the stereo-volume curve andstereo-shift curve. The computer-animated scene can then be filmed usingthe animated camera positions to produce a film sequence having thedesired stereo effect.

5. Smoothing a Scene Parameter Distribution for a Film Sequence

As discussed above with respect to process 1400, a computer-animatedfilm sequence can be created by animating a computer-generated scene andstereoscopically filming the animated scene using a pair of stereoscopiccameras. The resulting stereoscopic film sequence comprises a series ofimage frames, each image frame representing the computer-generated scenealong a film-sequence timeline.

Each image frame is also associated with a group of scene parametersthat define, inter alia, the position of the pair of stereoscopiccameras within the scene, and therefore the amount of stereo effect. Aspreviously discussed, the scene parameters may include cameraseparation, convergence distance, near-parallax, far-parallax, and thelike. Typically, the scene parameters change over time due to changes inthe composition of the scene, movement of the pair of cameras, or both.

FIG. 9 depicts a raw stereo curve 1020 including the values of threescene parameters (minimum scene depth, far-parallax, and near-parallax)over a film-sequence timeline 1010. The film-sequence timeline includesa plurality of time entries 1012. Each time entry 1012 represents amoment in time and is associated with corresponding image frame in thefilm sequence and a group of scene parameters.

As shown in FIG. 9, the scene parameters vary for each time entry 1012across the film-sequence timeline 1010. Raw stereo curve 1020 in FIG. 9represents the raw scene parameters over the film-sequence timeline1010. Raw stereo curve 1020 includes sharp rises or dramatic changes inthe scene parameters, which may result in stereo effect that appearswobbly or jittery for the corresponding film sequence. This effect maybe distracting and detract from the realism in the computer-animatedscene. To improve the stereo effect for a film sequence, it may bedesirable to smooth the values of the scene parameters over afilm-sequence timeline 1010.

FIG. 8 depicts and exemplary process 1500 for smoothing a stereoparameter for a computer-animated film sequence. The computer-animatedfilm sequence is typically defined with respect to a continuous sequenceof image frames depicting a computer-generated scene. Process 1500 isdescribed with respect to an exemplary stereo parameter, near-parallax.However, other stereo parameters could also be used and the process istypically repeated for more than one of the bounded-parallax constraints(e.g., minimum scene depth, maximum-scene depth, and far-parallax).

In general, process 1500 can be used to determine if the variation inthe stereo parameters for a film sequence is small enough that aconstant scene parameter can be used for the entire film sequence. Ifthe variation is too large, process 1500 can be used to apply asmoothing function to the stereo parameters to reduce the impact ofdrastic changes in scene parameter values.

In operation 1502, a film-sequence timeline is obtained for the filmsequence. The film-sequence timeline includes a plurality of timeentries that are associated with a plurality of image frames in the filmsequence. As discussed above, the time entries typically represent 1/24second timing intervals along the film-sequence timeline, although othertime intervals may be used and it is not necessary that the timeintervals be regularly spaced along the film-sequence timeline.

In process 1504, a scene parameter distribution is obtained for at leasttwo time entries of the plurality of time entries. In this example, thescene parameter distribution includes a near-parallax value for each ofthe at least two time entries. The near-parallax values can be obtainedfrom the raw stereo curve 1020 depicted in FIG. 9. These values may beobtained from computer memory or they may be obtained as an output ofanother process. As discussed above, processes 1100, 1300, and 1400 canall be used to obtain a near-parallax value for an image frame of thefilm sequence.

Alternatively, the near-parallax values may be obtained based on theexisting computer-generated scene configuration associated with each ofthe at least two time entries. In particular, equations 7 and 8discussed above, can be used to calculate the near-parallax value nsgiven a set of other scene parameters including the focal length of thepair of cameras f, the resolution of the camera sensors R_(c), the widthof the camera sensors W_(c), the camera separation t, the convergencedistance c, the minimum scene depth nd, and the maximum scene depth fd.

In operation 1506, a statistical measurement is calculated for the sceneparameter distribution. In this example, a standard deviation iscalculated for the distribution. There are various techniques forcalculating a standard deviation of a distribution of numbers. Equation13, below, depicts one exemplary technique for calculating the standarddeviation a for the distribution of far-parallax values fs:

$\begin{matrix}{{\sigma = {\sqrt{\frac{\sum\limits_{i = 1}^{n}{n\; s_{i}^{2}}}{n - 1}} - {\frac{n}{n - 1}\left( \frac{\sum\limits_{i = 1}^{n}{n\; s_{i}}}{n} \right)^{2}}}},} & (13)\end{matrix}$

where n is the number of time entries, and ns_(i) is the near-parallaxvalue for the i^(th) time entry. Generally, the standard deviation arepresents how much variation exists with respect to an average or meanof the scene parameter distribution. A low standard deviation indicatesthat the scene parameter values tend to be very close to the mean,whereas high standard deviation indicates that the scene parametervalues are spread over a larger range of values.

In operation 1508, the statistical measurement is compared to athreshold value. In this example, the scene parameter is thenear-parallax value and the threshold is measured in terms of a distancerelative to the size of the camera sensor or the display screen andexpressed in terms of a number of (screen or sensor) pixels. Thethreshold is used to determine if the variation in the near-parallaxvalues is small enough that a constant near-parallax value can be usedfor the entire film sequence. In some cases, a threshold value of 4.25pixels is an appropriate cutoff. In other cases, a threshold value of4.25 pixels or greater can be used. In some cases, a threshold value of4.25 pixels or less can be used. The threshold value, if measured inpixels, is relative to the resolution of the camera and/or screen andmay vary as the resolution of the camera and/or screen varies.

In operation 1510, a static scene parameter is calculated if thestatistical measurement is less than the threshold value. In thisexample, an average value is calculated as the static scene parameterbased on the scene parameter distribution. The average scene parametermay be computed as the arithmetic mean and expressed as:

$\begin{matrix}{{n\; s_{ave}} = {\frac{1}{n}{\sum\limits_{i = 1}^{n}{n\; s_{i}}}}} & (14)\end{matrix}$

where ns_(ave) is the average near-parallax, n is the number of timeentries, and ns_(i) is the near-parallax value for the i^(th) timeentry. Equation 16 represents an exemplary calculation and othertechniques can be used to calculate an average scene parameter. In otherembodiments, a statistical mean value may be calculated and used as thestatic scene parameter. Static stereo curve 1040 shown in FIG. 9 depictsan exemplary static near-parallax value over time.

In operation 1512, a set of smoothed scene parameters is calculatedbased on a smoothing function if the statistical measurement a isgreater than or equal to the threshold value. In this example, thesmoothing function is low-pass filter function that is applied to thescene parameter distribution to obtain a set of smoothed parameters. Theexample provided in equations 15, 16, and 17 below, demonstrates how asmoothed stereo curve is calculated by averaging each near-parallaxvalue ns_(i) by the two closest neighboring points on either side ofns_(i). Equation 17 depicts an exemplary mean filter:

ns _(filter)=[⅕, ⅕, ⅕, ⅕, ⅕].   (15)

Equation 18 depicts the convolution of ns_(filter) with a raw stereocurve ns:

ns _(smoothed) =ns _(filter) *ns.   (16)

Equation 19 depicts an exemplary computation of the an individualsmoothed value ns_(i), as an explicit implementation of the convolutionof equation 18:

$\begin{matrix}{{n\; s_{i\mspace{14mu} {smoothed}}} = {\frac{{n\; s_{i - 2}} + {n\; s_{i - 1}} + {n\; s_{i}} + {n\; s_{i + 1}} + {n\; s_{i + 2}}}{5}.}} & (17)\end{matrix}$

Equations 15, 16, and 17 depict an exemplary technique for calculating aset of smoothed parameters. Other techniques using other types offiltering and/or smoothing functions could also be used. For example, insome cases, hysteretic, anticipatory, and reactionary filteringtechniques could also be used.

FIG. 9 depicts an exemplary smoothed stereo curve 1030 that may resultfrom operation 1512. As compared to the raw stereo curve 1020, thesmoothed stereo curve 1030 does not exhibit sharp changes in the stereosettings across the film-sequence timeline 1010.

In operation 1514, the results are stored in computer memory. If thethreshold test of operation 1508 is not met, the static scene parametervalue is stored as the scene parameter value for each of the at leasttwo time entries. If the threshold test of operation 1508 is met, theset of smoothed scene parameter values are stored as the scene parametervalue for each of the at least two time entries.

Other scene parameters can also be computed based on the result ofprocess 1500. For example, as discussed above, equations 3 and 4 can beused to calculate a camera separation value and a convergence value forthe pair of cameras based on the near-parallax and far-parallax values.Also, as previously discussed, the camera separation value t and theconvergence distance value c may be used to position the pair ofstereoscopic cameras in the computer-generated scene. Specifically,equations 5 and 6, discussed above, demonstrate the relationship betweenthe convergence value c and parameters that directly specify theposition of the pair of stereoscopic cameras. By calculating a positionfor the pair of cameras for multiple time entries in the film-sequencetimeline, the camera position can be animated to produce the desiredstereo effect that corresponds to smoothed or static stereo curves. Thecomputer-animated scene can then be filmed using the animated camerapositions to produce a film sequence having the desired stereo effect.

9. Implementation on a Computer Hardware Platform

The embodiments described herein are typically implemented in the formof computer software (computer-executable instructions) executed on acomputer. FIG. 10 depicts an exemplary computer system 2000 configuredto perform any one of the above-described processes. In this context,computer system 2000 may be a general-purpose computer including, forexample, a processor, memory, storage, and input/output devices (e.g.,monitor, keyboard, disk drive, Internet connection, etc.). However,computer system 2000 may include circuitry or other specialized hardwarefor carrying out some or all aspects of the processes. In someoperational settings, computer system 2000 may be configured as a systemthat includes one or more units, each of which is configured to carryout some aspects of the processes either in software, in hardware, or insome combination thereof. For example, in some embodiments, the processfor computing the bounded-parallax constraints in accordance with theprocesses described above may be computed on parallel computerprocessors or performed on separate computer systems.

FIG. 10 depicts a computer system 2000 with a number of standardcomponents that may be used to perform the above-described processes.The main system 2002 includes a motherboard 2004 having an input/output(“I/O”) section 2006, one or more central processing units (“CPU”) 2008,and a memory section 2010, which may have a flash memory card 2012related to it. The I/O section 2006 is connected to a display 2024, akeyboard 2014, a disk storage unit 2016, and a media drive unit 2018.The media drive unit 2018 can read a computer-readable medium 2020,which typically contains computer-readable instructions 2022 and data.

At least some values based on the results of the above-describedprocesses can be saved for subsequent use. For example, the outputs ofthe system, including the bounded-parallax constraints, can be saveddirectly in memory 2010 (e.g, RAM (Random Access Memory)) or anotherform of storage, such as disk storage 2016. Additionally, values derivedfrom the bounded-parallax constraints, such as camera positions orimages of the computer-generated scene, can also be saved directly inmemory.

The above-described processes may be used to define the bounded-parallaxconstraints for a computer-generated scene. By computing thebounded-parallax constraints, a user can compose and stereoscopicallyfilm a computer-generated scene to produce a stereoscopic image thatdoes not require excessive convergence or divergence of the viewer'seyes. This stereoscopic image may be visualized as a still image or aspart of a film sequence. The stereoscopic image may be stored in memory2010 or disk storage 2016, or viewed on a computer display 2024.

Additionally, a non-transitory computer-readable medium can be used tostore (e.g., tangibly embody) one or more computer programs forperforming any one of the above-described processes by means of acomputer. The computer program may be written, for example, in ageneral-purpose programming language (e.g., Pascal, C, C++) or somespecialized application-specific language.

Although the invention has been described in considerable detail withreference to certain embodiments thereof, other embodiments arepossible, as will be understood to those skilled in the art.

What is claimed is:
 1. A computer-implemented method for smoothing astereo parameter for a computer-animated film sequence, the methodcomprising: obtaining a timeline for the film sequence, the timelinecomprising a plurality of time entries; obtaining a stereo parameterdistribution, wherein the stereo parameter distribution comprises onestereo parameter value for at least two time entries of the plurality oftime entries, and wherein the stereo parameter value corresponds to astereo setting associated with a pair of stereoscopic cameras configuredto produce a stereoscopic image of the computer-animated film sequence;calculating a statistical measurement of the stereo parameterdistribution; if the statistical measurement is less than a thresholdvalue: calculating a static scene parameter based on the stereoparameter values of the parameter distribution, and storing, in acomputer memory, the static scene parameter as the stereo parametervalue for each of the at least two time entries; and if the statisticalmeasurement is greater than or equal to a threshold value: calculating aset of smoothed parameter values based on the parameter distribution anda smoothing function, and storing, in the computer memory, the set ofsmoothed parameter values as the stereo parameter value for each of theat least two time entries.
 2. The computer-implemented method of claim1, further comprising: positioning each camera of the pair ofstereoscopic cameras relative to each other based on the smoothedparameter values; creating a stereoscopic film sequence of thecomputer-generated scene with the pair of stereoscopic cameras; andstoring, in the computer memory, the stereoscopic film sequence.
 3. Thecomputer-implemented method of claim 1, further comprising: calculatinga camera separation value and a convergence value for the pair ofstereoscopic cameras based on the set of smoothed parameter values; andstoring, in the computer memory, the camera separation value and theconvergence value.
 4. The computer-implemented method of claim 3,further comprising: positioning each camera of the pair of stereoscopiccameras relative to each other within the computer-generated scene basedon the camera separation value and the convergence value.
 5. Thecomputer-implemented method of claim 3, further comprising positioning acamera sensor of the pair of stereoscopic cameras within thecomputer-generated scene based on the camera separation value and theconvergence value.
 6. The computer-implemented method of claim 1,wherein the statistical measurement is a standard deviation.
 7. Thecomputer-implemented method of claim 1, wherein, if the statisticalmeasurement is less than a threshold value, calculating the static sceneparameter by taking an average of the stereo parameter values of theparameter distribution.
 8. The computer-implemented method of claim 1,wherein, if the statistical measurement is less than a threshold value,calculating the static scene parameter by taking a statistical mean ofthe stereo parameter values of the parameter distribution.
 9. Thecomputer-implemented method of claim 1, wherein, if the statisticalmeasurement is greater than a threshold value, calculating the set ofsmoothed parameter values based on the parameter distribution and alow-pass filter function.
 10. A computer system for smoothing a stereoparameter for a computer-animated film sequence, the system comprising:a computer memory; a processor for executing computer-readableinstructions, the instructions for: obtaining a timeline for the filmsequence, the timeline comprising a plurality of time entries; obtaininga stereo parameter distribution, wherein the stereo parameterdistribution comprises one stereo parameter value for at least two timeentries of the plurality of time entries, and wherein the stereoparameter value corresponds to a stereo setting associated with a pairof stereoscopic cameras configured to produce a stereoscopic image ofthe computer-animated film sequence; calculating a statisticalmeasurement of the stereo parameter distribution; if the statisticalmeasurement is less than a threshold value: calculating a static sceneparameter based on the stereo parameter values of the parameterdistribution, storing, in the computer memory, the static sceneparameter as the stereo parameter value for each of the at least twotime entries; and if the statistical measurement is greater than orequal to a threshold value: calculating a set of smoothed parametervalues based on the parameter distribution and a smoothing function, andstoring, in the computer memory, the set of smoothed parameter values asthe stereo parameter value for each of the at least two time entries.11. The computer system of claim 10, the instructions furthercomprising: positioning each camera of the pair of stereoscopic camerasrelative to each other based on the smoothed parameter values; creatinga stereoscopic film sequence of the computer-generated scene with thepair of stereoscopic cameras; and storing, in the computer memory, thestereoscopic film sequence.
 12. The computer system of claim 10, theinstructions further comprising: calculating a camera separation valueand a convergence value for the pair of stereoscopic cameras based onscript-adjusted near-parallax value and script-adjusted far-parallaxvalue; and storing, in the computer memory, the camera separation valueand the convergence value.
 13. The computer system of claim 1, whereinthe statistical measurement is a standard deviation.
 14. The computersystem of claim 10, wherein, if the statistical measurement is less thana threshold value, calculating the static scene parameter by taking anaverage of the stereo parameter values of the parameter distribution.15. The computer system of claim 10, wherein, if the statisticalmeasurement is less than a threshold value, calculating the static sceneparameter by taking a statistical mean of the stereo parameter values ofthe parameter distribution.
 16. The computer system of claim 10,wherein, if the statistical measurement is greater than a thresholdvalue, calculating the set of smoothed parameter values based on theparameter distribution and a low-pass filter function.
 17. Anon-transitory computer-readable storage medium includingcomputer-readable instructions that when executed on a computerprocessor cause the computer processor to smooth a stereo parametervalue for a computer-animated film sequence, the instructionscomprising: obtaining a timeline for the film sequence, the timelinecomprising a plurality of time entries; obtaining a stereo parameterdistribution, wherein the stereo parameter distribution comprises onestereo parameter value for at least two time entries of the plurality oftime entries, and wherein the stereo parameter value corresponds to astereo setting associated with a pair of stereoscopic cameras configuredto produce a stereoscopic image of the computer-animated film sequence;calculating a statistical measurement of the stereo parameterdistribution; if the statistical measurement is less than a thresholdvalue: calculating a static scene parameter based on the stereoparameter values of the parameter distribution, storing, in a computermemory, the static scene parameter as the stereo parameter value foreach of the at least two time entries; and if the statisticalmeasurement is greater than or equal to a threshold value: calculating aset of smoothed parameter values based on the parameter distribution anda smoothing function, and storing, in the computer memory, the set ofsmoothed parameter values as the stereo parameter value for each of theat least two time entries.
 18. The non-transitory computer-readablestorage medium of claim 17, the instructions further comprising:positioning each camera of the pair of stereoscopic cameras relative toeach other based on the smoothed parameter values; creating astereoscopic film sequence of the computer-generated scene with the pairof stereoscopic cameras; and storing, in the computer memory, thestereoscopic film sequence.
 19. The non-transitory computer-readablestorage medium of claim 17, the instructions further comprising:calculating a camera separation value and a convergence value for thepair of stereoscopic cameras based on script-adjusted near-parallaxvalue and script-adjusted far-parallax value; and storing, in thecomputer memory, the camera separation value and the convergence value.20. The non-transitory computer-readable storage medium of claim 17,wherein the statistical measurement is a standard deviation.
 21. Thenon-transitory computer-readable storage medium of claim 17, wherein, ifthe statistical measurement is less than a threshold value, calculatingthe static scene parameter by taking an average of the stereo parametervalues of the parameter distribution.
 22. The non-transitorycomputer-readable storage medium of claim 17, wherein, if thestatistical measurement is less than a threshold value, calculating thestatic scene parameter by taking a statistical mean of the stereoparameter values of the parameter distribution.
 23. The non-transitorycomputer-readable storage medium of claim 17, wherein, if thestatistical measurement is greater than a threshold value, calculatingthe set of smoothed parameter values based on the parameter distributionand a low-pass filter function.